Presence detection and tdoa estimation of spread spectrum signals using sensor array

In this thesis, the presence detection and time di fference of arrival (TDOA) estimation of direct-sequence spread spectrum signals (DS-SS) in low signal to noise ratio (SNR) using the sensor array are considered. Two different methods are proposed for the presence detection of both the long and short code DS-SS signals. The fi rst proposed method is based on the phase linearity of the cross channel terms of the spatial covariance (R) matrices. The second detection method uses the eigenvalue ratios of the R matrices which is a known approach in literature. But to our knowledge this approach is firstly applied to long code DS-SS signals in this thesis. In addition, a new sample R matrix estimation technique, which is called as block of consecutive frequency bins (BCFB), is proposed. It is also shown that using the R matrix of the proposed BCFB method improves the detection performance especially in low SNR. In the second part of the thesis, TDOA of the received signals is also estimated using only the phase slope of the estimated R matrices in the first proposed detection method. In this way, by using the proposed presence detection method, it is also possible to estimate the TDOA between the sensors. In simulations, it is shown that the proposed TDOA estimators performance is effi cient in low SNR and it attains to the Cramer Rao Lower Bound (CRLB).